{"id":"W2597475300","doi":"10.19026/rjaset.13.3344","title":"Development of LiDAR Database Management System using Open Source Software","year":2016,"lang":"en","type":"article","venue":"Research Journal of Applied Sciences Engineering and Technology","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"British Columbia Institute of Technology","keywords":"Lidar; Computer science; Database; Software; Data management; Interactivity; Open data; Management system; Remote sensing; World Wide Web; Engineering; Operating system; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001540091,0.00009074078,0.0001892801,0.0008276828,0.0001460989,0.00003745016,0.0008089631,0.00006317613,0.000002129094],"category_scores_gemma":[0.00003549328,0.00006621057,0.0000125696,0.0008206877,0.000194532,0.0001079158,0.0004219979,0.0001925631,0.000002388659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001193341,"about_ca_system_score_gemma":0.00007669332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001807918,"about_ca_topic_score_gemma":8.291615e-7,"domain_scores_codex":[0.9988126,0.000005914713,0.0003623758,0.0001488729,0.0003691357,0.0003010604],"domain_scores_gemma":[0.9994636,0.00008240361,0.00006549989,0.0001876762,0.0001261885,0.00007462473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001665109,0.000046821,0.0001261385,0.0007225916,0.0001558186,0.00001568637,0.000307477,0.1897611,0.5361874,0.0608599,0.00006535412,0.2117351],"study_design_scores_gemma":[0.002343254,0.0002810301,0.0001295932,0.004479859,0.00006591179,0.0003839421,0.004564442,0.4138762,0.541514,0.00260916,0.02883222,0.0009202861],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3266313,0.0002091987,0.6725963,0.00004010542,0.00004250576,0.0001698705,0.000002298641,0.00008785095,0.0002205825],"genre_scores_gemma":[0.6186752,0.00004510312,0.38124,3.676694e-7,0.00001218813,0.00001322251,1.199285e-7,0.000009968543,0.000003844496],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.292044,"threshold_uncertainty_score":0.2699989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05038945047077314,"score_gpt":0.307940223867686,"score_spread":0.2575507733969128,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}